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Nowcasting Norway

Authors: Luciani, Matteo; Ricci, Lorenzo;

Nowcasting Norway

Abstract

We produce predictions of the previous, the current, and the next quarter of NorwegianGDP. To this end, we estimate a Bayesian Dynamic Factor model on a panel of 14variables (all followed closely by market operators) ranging from 1990 to 2011. By meansof a real time forecasting exercise we show that the Bayesian Dynamic Factor Model outperformsa standard benchmark model, while it performs equally well than the BloombergSurvey. Additionally, we use our model to produce annual GDP growth rate nowcast. Weshow that our annual nowcast outperform the Norges Bank’s projections of current yearGDP.

info:eu-repo/semantics/published

Country
Belgium
Keywords

Prices, bayesian factor model, E37, Multiple or Simultaneous Equation Models: Time-Series Models, nowcasting, real-time forecasting; bayesian factor model; nowcasting, Forecasting and Other Model Applications, Business Fluctuations, and Cycles: Forecasting and Simulation, Finance internationale, Economie, Econométrie et méthodes statistiques :théorie et applications, real-time forecasting, C53, C32, Prices, Business Fluctuations, and Cycles: Forecasting and Simulation, jel: jel:C53, jel: jel:C32, jel: jel:E37

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    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Average
Average
Top 10%
Green